Clinical Data Workbenches: An Evolving Product Category Speeds Access To Quality Data

The rise in third-party patient data has driven the development of clinical data workbenches, aiming to ensure data quality, enhance analytics utilization, and reduce reliance on manual aggregation, cleaning, and transformation. Today's clinical trials heavily depend on the quality of supporting data, yet around 70% of this data originates from diverse sources like labs, wearable devices, and ePRO solutions, posing challenges for traditional CRFs and EDC systems.

To cope, organizations have deployed global teams utilizing manual methods, statistical tools, spreadsheets, and extensive email exchanges for data aggregation, cleaning, and transformation. Despite these efforts, managing the increasing volumes of external patient data, especially in complex trial designs like genomics trials generating large datasets, remains a challenge.

Manual processes are prone to inconsistencies and lack of documentation, raising concerns about data quality and regulatory scrutiny. To improve efficiency and ensure reliable data access, clinical data scientists are focusing on enhancing upstream data ingestion, cleaning, and transformation, as well as refining downstream clinical and operational analytics capabilities.

Amid these challenges, clinical data workbenches are emerging as critical tools to streamline these tasks, supporting more agile and compliant clinical trial operations. Discover how the exponential increase in third-party patient data has catalyzed the emergence of the clinical data workbench by downloading the ebook below.